Computer-aided diagnosis for identifying and delineating early gastric cancers in magnifying narrow-band imaging.
Gastrointest Endosc
; 87(5): 1339-1344, 2018 May.
Article
in En
| MEDLINE
| ID: mdl-29225083
ABSTRACT
BACKGROUND AND AIMS:
Magnifying narrow-band imaging (M-NBI) is important in the diagnosis of early gastric cancers (EGCs) but requires expertise to master. We developed a computer-aided diagnosis (CADx) system to assist endoscopists in identifying and delineating EGCs.METHODS:
We retrospectively collected and randomly selected 66 EGC M-NBI images and 60 non-cancer M-NBI images into a training set and 61 EGC M-NBI images and 20 non-cancer M-NBI images into a test set. After preprocessing and partition, we determined 8 gray-level co-occurrence matrix (GLCM) features for each partitioned 40 × 40 pixel block and calculated a coefficient of variation of 8 GLCM feature vectors. We then trained a support vector machine (SVMLv1) based on variation vectors from the training set and examined in the test set. Furthermore, we collected 2 determined P and Q GLCM feature vectors from cancerous image blocks containing irregular microvessels from the training set, and we trained another SVM (SVMLv2) to delineate cancerous blocks, which were compared with expert-delineated areas for area concordance.RESULTS:
The diagnostic performance revealed accuracy of 96.3%, precision (positive predictive value [PPV]) of 98.3%, recall (sensitivity) of 96.7%, and specificity of 95%, at a rate of 0.41 ± 0.01 seconds per image. The performance of area concordance, on a block basis, demonstrated accuracy of 73.8% ± 10.9%, precision (PPV) of 75.3% ± 20.9%, recall (sensitivity) of 65.5% ± 19.9%, and specificity of 80.8% ± 17.1%, at a rate of 0.49 ± 0.04 seconds per image.CONCLUSIONS:
This pilot study demonstrates that our CADx system has great potential in real-time diagnosis and delineation of EGCs in M-NBI images.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Stomach Neoplasms
/
Image Processing, Computer-Assisted
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Diagnosis, Computer-Assisted
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Gastroscopy
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Narrow Band Imaging
Type of study:
Diagnostic_studies
/
Observational_studies
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Risk_factors_studies
/
Screening_studies
Limits:
Aged
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Female
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Humans
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Male
/
Middle aged
Language:
En
Journal:
Gastrointest Endosc
Year:
2018
Type:
Article
Affiliation country:
Japan